{"id":251061,"date":"2026-10-09T11:58:01","date_gmt":"2026-10-09T06:28:01","guid":{"rendered":"https:\/\/www.oliveboard.in\/blog\/?p=251061"},"modified":"2026-10-09T11:58:03","modified_gmt":"2026-10-09T06:28:03","slug":"pfrda-grade-a-ai-ml-quiz","status":"publish","type":"post","link":"https:\/\/www.oliveboard.in\/blog\/pfrda-grade-a-ai-ml-quiz\/","title":{"rendered":"Attempt PFRDA Grade A 2026 AI\/ML Practice Quiz and Download PDF"},"content":{"rendered":"<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_77 counter-hierarchy ez-toc-counter ez-toc-grey ez-toc-container-direction\">\n<div class=\"ez-toc-title-container\">\n<p class=\"ez-toc-title\" style=\"cursor:inherit\">Table of content<\/p>\n<span class=\"ez-toc-title-toggle\"><a href=\"#\" class=\"ez-toc-pull-right ez-toc-btn ez-toc-btn-xs ez-toc-btn-default ez-toc-toggle\" aria-label=\"Toggle Table of Content\"><span class=\"ez-toc-js-icon-con\"><span class=\"\"><span class=\"eztoc-hide\" style=\"display:none;\">Toggle<\/span><span class=\"ez-toc-icon-toggle-span\"><svg style=\"fill: #999;color:#999\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" class=\"list-377408\" width=\"20px\" height=\"20px\" viewBox=\"0 0 24 24\" fill=\"none\"><path d=\"M6 6H4v2h2V6zm14 0H8v2h12V6zM4 11h2v2H4v-2zm16 0H8v2h12v-2zM4 16h2v2H4v-2zm16 0H8v2h12v-2z\" fill=\"currentColor\"><\/path><\/svg><svg style=\"fill: #999;color:#999\" class=\"arrow-unsorted-368013\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"10px\" height=\"10px\" viewBox=\"0 0 24 24\" version=\"1.2\" baseProfile=\"tiny\"><path d=\"M18.2 9.3l-6.2-6.3-6.2 6.3c-.2.2-.3.4-.3.7s.1.5.3.7c.2.2.4.3.7.3h11c.3 0 .5-.1.7-.3.2-.2.3-.5.3-.7s-.1-.5-.3-.7zM5.8 14.7l6.2 6.3 6.2-6.3c.2-.2.3-.5.3-.7s-.1-.5-.3-.7c-.2-.2-.4-.3-.7-.3h-11c-.3 0-.5.1-.7.3-.2.2-.3.5-.3.7s.1.5.3.7z\"\/><\/svg><\/span><\/span><\/span><\/a><\/span><\/div>\n<nav><ul class='ez-toc-list ez-toc-list-level-1 eztoc-toggle-hide-by-default' ><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-1\" href=\"https:\/\/www.oliveboard.in\/blog\/pfrda-grade-a-ai-ml-quiz\/#Download_PFRDA_Grade_A_AIML_Practice_Quiz_PDF\" >Download PFRDA Grade A AI\/ML Practice Quiz PDF<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/www.oliveboard.in\/blog\/pfrda-grade-a-ai-ml-quiz\/#Attempt_PFRDA_Grade_A_AIML_Practice_Quiz\" >Attempt PFRDA Grade A AI\/ML Practice Quiz<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/www.oliveboard.in\/blog\/pfrda-grade-a-ai-ml-quiz\/#Sign_Up\" >Sign Up<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/www.oliveboard.in\/blog\/pfrda-grade-a-ai-ml-quiz\/#Login\" >Login<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-5\" href=\"https:\/\/www.oliveboard.in\/blog\/pfrda-grade-a-ai-ml-quiz\/#Forgot_Password\" >Forgot Password<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-6\" href=\"https:\/\/www.oliveboard.in\/blog\/pfrda-grade-a-ai-ml-quiz\/#i\" >&nbsp;<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-7\" href=\"https:\/\/www.oliveboard.in\/blog\/pfrda-grade-a-ai-ml-quiz\/#What_is_the_AIML_syllabus_for_PFRDA_Grade_A_2026\" >What is the AI\/ML syllabus for PFRDA Grade A 2026?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-8\" href=\"https:\/\/www.oliveboard.in\/blog\/pfrda-grade-a-ai-ml-quiz\/#What_is_Machine_Learning\" >What is Machine Learning?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-9\" href=\"https:\/\/www.oliveboard.in\/blog\/pfrda-grade-a-ai-ml-quiz\/#What_is_Supervised_Learning\" >What is Supervised Learning?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-10\" href=\"https:\/\/www.oliveboard.in\/blog\/pfrda-grade-a-ai-ml-quiz\/#What_is_Unsupervised_Learning\" >What is Unsupervised Learning?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-11\" href=\"https:\/\/www.oliveboard.in\/blog\/pfrda-grade-a-ai-ml-quiz\/#What_is_Data_Preprocessing\" >What is Data Preprocessing?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-12\" href=\"https:\/\/www.oliveboard.in\/blog\/pfrda-grade-a-ai-ml-quiz\/#What_is_Model_Evaluation\" >What is Model Evaluation?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-13\" href=\"https:\/\/www.oliveboard.in\/blog\/pfrda-grade-a-ai-ml-quiz\/#What_are_Overfitting_and_Underfitting\" >What are Overfitting and Underfitting?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-14\" href=\"https:\/\/www.oliveboard.in\/blog\/pfrda-grade-a-ai-ml-quiz\/#What_is_Cross-Validation_in_Machine_Learning\" >What is Cross-Validation in Machine Learning?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-15\" href=\"https:\/\/www.oliveboard.in\/blog\/pfrda-grade-a-ai-ml-quiz\/#What_is_NLP_in_AIML\" >What is NLP in AI\/ML?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-16\" href=\"https:\/\/www.oliveboard.in\/blog\/pfrda-grade-a-ai-ml-quiz\/#What_is_Sentiment_Analysis\" >What is Sentiment Analysis?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-17\" href=\"https:\/\/www.oliveboard.in\/blog\/pfrda-grade-a-ai-ml-quiz\/#What_are_Large_Language_Models_LLMs\" >What are Large Language Models (LLMs)?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-18\" href=\"https:\/\/www.oliveboard.in\/blog\/pfrda-grade-a-ai-ml-quiz\/#What_is_Agentic_AI\" >What is Agentic AI?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-19\" href=\"https:\/\/www.oliveboard.in\/blog\/pfrda-grade-a-ai-ml-quiz\/#What_is_Responsible_AI\" >What is Responsible AI?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-20\" href=\"https:\/\/www.oliveboard.in\/blog\/pfrda-grade-a-ai-ml-quiz\/#What_is_Reinforcement_Learning\" >What is Reinforcement Learning?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-21\" href=\"https:\/\/www.oliveboard.in\/blog\/pfrda-grade-a-ai-ml-quiz\/#FAQs\" >FAQs<\/a><\/li><\/ul><\/nav><\/div>\n\n<p>The <strong>PFRDA Grade A 2026 AI\/ML Practice Quiz<\/strong> is designed to help candidates revise the newly added Artificial Intelligence and Machine Learning topics in the General Stream Paper 2 syllabus. AI\/ML is one of the major additions to the 2026 syllabus, making it important for candidates to understand both basic concepts and their practical applications. <\/p>\n\n\n\n<p>The quiz covers topics such as machine learning, data preprocessing, model evaluation, NLP, LLMs, Generative AI, Agentic AI, reinforcement learning, and Responsible AI. Regular practice can help candidates improve conceptual clarity and accuracy while preparing for the Paper 2 exam.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-download-pfrda-grade-a-ai-ml-practice-quiz-pdf\"><span class=\"ez-toc-section\" id=\"Download_PFRDA_Grade_A_AIML_Practice_Quiz_PDF\"><\/span>Download PFRDA Grade A AI\/ML Practice Quiz PDF<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>The PFRDA Grade A AI\/ML Practice Quiz PDF provides practice questions based on the major AI and Machine Learning concepts included in the 2026 General Stream syllabus. Candidates can use the PDF for quick revision and practice after completing the basic concepts.<\/p>\n\n\n\n<figure class=\"wp-block-table\"><table><tbody><tr><td><strong>Particulars<\/strong><\/td><td><strong>Link<\/strong><\/td><\/tr><tr><td>PFRDA Grade A AI\/ML Practice Quiz Set 1<\/td><td><a href=\"https:\/\/www.oliveboard.in\/pfrda-grade-a-prep-kit\/?ref=contac-pfrda-ai-ml-pq\" target=\"_blank\" rel=\"noreferrer noopener\">Download Now<\/a><\/td><\/tr><tr><td>PFRDA Grade A AI\/ML Practice Quiz Set 2<\/td><td><a href=\"https:\/\/www.oliveboard.in\/100-mcqs-on-ai-ml-module-for-pfrda-grade-a-exam\/?ref=contac-pfrda-ai-ml-pq\" target=\"_blank\" rel=\"noreferrer noopener\">Download Now<\/a><\/td><\/tr><tr><td>PFRDA Grade A Stream Wise PYPs<\/td><td><a href=\"https:\/\/www.oliveboard.in\/blog\/pfrda-assistant-manager-previous-year-paper\/?ref=contac-pfrda-ai-ml-pq\" target=\"_blank\" rel=\"noreferrer noopener\">Download Now<\/a><\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-attempt-pfrda-grade-a-ai-ml-practice-quiz\"><span class=\"ez-toc-section\" id=\"Attempt_PFRDA_Grade_A_AIML_Practice_Quiz\"><\/span>Attempt PFRDA Grade A AI\/ML Practice Quiz<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>Attempt the free AI\/ML practice quiz to check your preparation level and identify topics that need more revision. Since AI\/ML has been newly added to the <a href=\"https:\/\/www.oliveboard.in\/blog\/pfrda-assistant-manager-syllabus\/?ref=contac-pfrda-ai-ml-pq\" target=\"_blank\" rel=\"noreferrer noopener\">PFRDA Grade A 2026 syllabus<\/a>, candidates should focus on understanding concepts instead of relying only on memorisation.<\/p>\n\n\n\n<!DOCTYPE html>\n<html lang=\"en\">\n<head>\n<meta charset=\"UTF-8\">\n<link rel=\"stylesheet\" href=\"https:\/\/courses.oliveboard.in\/edge\/css\/login-modal-for-blog.css\">\n\n<style>\n#quiz-1-sticky-header {\n  position: sticky;\n  top: 0;\n  z-index: 100;\n  background: #1565c0;\n  color: #fff;\n  padding: 12px 20px;\n  border-radius: 10px 10px 0 0;\n  display: flex;\n  justify-content: space-between;\n  align-items: center;\n  font-size: 16px;\n  font-weight: bold;\n  box-shadow: 0 2px 8px rgba(0,0,0,0.2);\n  margin: -20px -20px 20px -20px;\n}\n\n#quiz-1-score-badge {\n  background: rgba(255,255,255,0.2);\n  padding: 4px 12px;\n  border-radius: 20px;\n  font-size: 15px;\n  white-space: nowrap;\n}\n#quiz-1 * { box-sizing: border-box; }\n\n#quiz-1 .quiz-container {\n  max-width: 700px;\n  margin: auto;\n  padding: 20px;\n  background: #fff;\n  border-radius: 14px;\n  box-shadow: 0 6px 16px rgba(0,0,0,0.12);\n}\n\n#quiz-1 h2 {\n  text-align: center;\n}\n\n#quiz-1 .question {\n  margin-bottom: 22px;\n}\n\n#quiz-1 .question p {\n  font-weight: bold;\n}\n\n#quiz-1 button {\n  width: 100%;\n  padding: 12px;\n  margin: 6px 0;\n  border: none;\n  border-radius: 6px;\n  background: #e0e0e0;\n  color: #000;\n  font-size: 16px;\n  cursor: pointer;\n}\n\n#quiz-1 button:hover {\n  background: #d5d5d5;\n}\n\n#quiz-1 button.correct {\n  background: #4caf50;\n  color: #000;\n}\n\n#quiz-1 button.wrong {\n  background: #f44336;\n  color: #000;\n}\n\n#quiz-1 button.locked {\n  pointer-events: none;\n}\n\n\/* SUMMARY *\/\n#quiz-1 .final-summary {\n  margin-top: 40px;\n  padding: 20px;\n  border-radius: 14px;\n  background: #fafafa;\n  border: 2px solid #4caf50;\n}\n\n#quiz-1 .final-summary h3 {\n  text-align: center;\n  margin-bottom: 20px;\n}\n\n#quiz-1 .summary-row {\n  display: grid;\n  grid-template-columns: 120px 1fr 40px;\n  gap: 10px;\n  align-items: center;\n  margin-bottom: 12px;\n  font-weight: bold;\n}\n\n#quiz-1 .summary-bar {\n  height: 14px;\n  background: #ddd;\n  border-radius: 10px;\n  overflow: hidden;\n}\n\n#quiz-1 .bar-fill {\n  height: 100%;\n  width: 0%;\n}\n\n#quiz-1 .bar-attempted { background: #2196f3; }\n#quiz-1 .bar-correct { background: #4caf50; }\n#quiz-1 .bar-wrong { background: #f44336; }\n#quiz-1 .bar-unattempted { background: #9e9e9e; width: 100%; }\n\n#quiz-1 .final-score {\n  text-align: center;\n  font-size: 22px;\n  margin-top: 20px;\n}\n\n#quiz-1 .score-value {\n  font-size: 30px;\n  margin-left: 8px;\n}\n<\/style>\n<\/head>\n\n<body>\n<div id=\"quiz-1\">\n  <div class=\"quiz-container\">\n<div id=\"quiz-1-sticky-header\">\n  <span> PFRDA Grade A AI\/ML Practice Quiz <\/span>\n  <span id=\"quiz-1-score-badge\">Score: <strong id=\"quiz-1-score-value\">0.00<\/strong><\/span>\n<\/div>\n\n    <!-- QUESTIONS -->\n\n<div class=\"question\" data-answered=\"false\">\n  <p>1. Which statement best describes Artificial Intelligence (AI)?<\/p>\n  <button data-correct=\"true\">It is the broad field of building systems that perform tasks requiring humanlike intelligence.<\/button>\n  <button data-correct=\"false\">It is only the use of spreadsheets for statistical analysis.<\/button>\n  <button data-correct=\"false\">It refers only to robots that physically resemble humans.<\/button>\n  <button data-correct=\"false\">It is a synonym for database management.<\/button>\n  <button data-correct=\"false\">It is limited to rule-based expert systems and excludes learning systems.<\/button>\n<\/div>\n\n<div class=\"question\" data-answered=\"false\">\n  <p>2. Which relationship among AI, Machine Learning and Deep Learning is most accurate?<\/p>\n  <button data-correct=\"false\">AI is a subset of Deep Learning, which is a subset of Machine Learning.<\/button>\n  <button data-correct=\"true\">Deep Learning is a subset of Machine Learning, which is a subset of AI.<\/button>\n  <button data-correct=\"false\">Machine Learning and AI are unrelated disciplines.<\/button>\n  <button data-correct=\"false\">Deep Learning contains all of AI and all of statistics.<\/button>\n  <button data-correct=\"false\">Machine Learning is a subset of databases rather than AI.<\/button>\n<\/div>\n\n<div class=\"question\" data-answered=\"false\">\n  <p>3. In traditional rule-based programming, how are outputs primarily produced?<\/p>\n  <button data-correct=\"false\">The system learns all rules automatically from labelled examples.<\/button>\n  <button data-correct=\"false\">The model always uses reinforcement signals instead of rules.<\/button>\n  <button data-correct=\"true\">Programmers explicitly specify rules that transform inputs into outputs.<\/button>\n  <button data-correct=\"false\">The system cannot accept numerical inputs.<\/button>\n  <button data-correct=\"false\">Outputs are generated only by large language models.<\/button>\n<\/div>\n\n<div class=\"question\" data-answered=\"false\">\n  <p>4. In machine learning, what is a feature?<\/p>\n  <button data-correct=\"false\">The final predicted value produced by the model.<\/button>\n  <button data-correct=\"false\">A legal restriction placed on model deployment.<\/button>\n  <button data-correct=\"false\">A metric used only for regression evaluation.<\/button>\n  <button data-correct=\"true\">An input variable or measurable attribute used by a model to make a prediction.<\/button>\n  <button data-correct=\"false\">A fixed hardware component in an AI server.<\/button>\n<\/div>\n\n<div class=\"question\" data-answered=\"false\">\n  <p>5. What is meant by inference in a machine-learning system?<\/p>\n  <button data-correct=\"false\">Deleting the training dataset after model creation.<\/button>\n  <button data-correct=\"false\">Changing labels in the training data manually.<\/button>\n  <button data-correct=\"false\">Calculating only the training loss before learning starts.<\/button>\n  <button data-correct=\"false\">Replacing all features with random values.<\/button>\n  <button data-correct=\"true\">Using a trained model to generate predictions on new data.<\/button>\n<\/div>\n\n<div class=\"question\" data-answered=\"false\">\n  <p>6. Which of the following is primarily a regression task?<\/p>\n  <button data-correct=\"true\">Predicting the expected rupee value of a customer&#8217;s monthly expenditure.<\/button>\n  <button data-correct=\"false\">Classifying an email as spam or not spam.<\/button>\n  <button data-correct=\"false\">Assigning a transaction to one of five fraud categories.<\/button>\n  <button data-correct=\"false\">Grouping customers into segments without labels.<\/button>\n  <button data-correct=\"false\">Detecting whether a face matches a known identity.<\/button>\n<\/div>\n\n<div class=\"question\" data-answered=\"false\">\n  <p>7. Which of the following is primarily a classification task?<\/p>\n  <button data-correct=\"false\">Estimating the exact market price of a bond tomorrow.<\/button>\n  <button data-correct=\"true\">Predicting whether a loan applicant will default or not default.<\/button>\n  <button data-correct=\"false\">Forecasting the number of transactions in the next hour.<\/button>\n  <button data-correct=\"false\">Estimating a customer&#8217;s annual income as a continuous value.<\/button>\n  <button data-correct=\"false\">Calculating the expected loss amount in rupees.<\/button>\n<\/div>\n\n<div class=\"question\" data-answered=\"false\">\n  <p>8. What is a model parameter in machine learning?<\/p>\n  <button data-correct=\"false\">A user-selected setting such as the learning rate.<\/button>\n  <button data-correct=\"false\">A label that is manually attached to every prediction after deployment.<\/button>\n  <button data-correct=\"true\">A value learned from training data, such as a regression coefficient or neural-network weight.<\/button>\n  <button data-correct=\"false\">A data-cleaning rule that must never change.<\/button>\n  <button data-correct=\"false\">A performance metric chosen after testing.<\/button>\n<\/div>\n\n<div class=\"question\" data-answered=\"false\">\n  <p>9. What is a hyperparameter?<\/p>\n  <button data-correct=\"false\">A model coefficient estimated directly from the training examples.<\/button>\n  <button data-correct=\"false\">The true target value in a labelled dataset.<\/button>\n  <button data-correct=\"false\">A mandatory legal disclosure for every AI model.<\/button>\n  <button data-correct=\"true\">A configuration value selected for the learning process, such as tree depth or learning rate.<\/button>\n  <button data-correct=\"false\">A test-set prediction that has been manually corrected.<\/button>\n<\/div>\n\n<div class=\"question\" data-answered=\"false\">\n  <p>10. What does model generalization refer to?<\/p>\n  <button data-correct=\"false\">The ability to memorize every training example exactly.<\/button>\n  <button data-correct=\"false\">The ability to increase the number of features without limit.<\/button>\n  <button data-correct=\"false\">The ability to avoid using any validation data.<\/button>\n  <button data-correct=\"false\">The ability to generate only deterministic outputs.<\/button>\n  <button data-correct=\"true\">The ability of a model to perform well on new, unseen data.<\/button>\n<\/div>\n\n<div class=\"question\" data-answered=\"false\">\n  <p>11. What is the defining characteristic of supervised learning?<\/p>\n  <button data-correct=\"true\">The training data contain input examples paired with known target labels or values.<\/button>\n  <button data-correct=\"false\">The training data contain no target information at all.<\/button>\n  <button data-correct=\"false\">The agent learns only from rewards produced by an environment.<\/button>\n  <button data-correct=\"false\">The model is never evaluated against known outcomes.<\/button>\n  <button data-correct=\"false\">The system can operate only on text data.<\/button>\n<\/div>\n\n<div class=\"question\" data-answered=\"false\">\n  <p>12. Which algorithm is most directly associated with predicting a continuous target using a linear relationship?<\/p>\n  <button data-correct=\"false\">K-Means Clustering<\/button>\n  <button data-correct=\"true\">Linear Regression<\/button>\n  <button data-correct=\"false\">Apriori Association Mining<\/button>\n  <button data-correct=\"false\">DBSCAN<\/button>\n  <button data-correct=\"false\">Principal Component Analysis<\/button>\n<\/div>\n\n<div class=\"question\" data-answered=\"false\">\n  <p>13. Despite its name, Logistic Regression is commonly used for which task?<\/p>\n  <button data-correct=\"false\">Unsupervised clustering<\/button>\n  <button data-correct=\"false\">Dimensionality reduction<\/button>\n  <button data-correct=\"true\">Classification<\/button>\n  <button data-correct=\"false\">Association-rule mining<\/button>\n  <button data-correct=\"false\">Image compression only<\/button>\n<\/div>\n\n<div class=\"question\" data-answered=\"false\">\n  <p>14. What is a decision tree designed to do?<\/p>\n  <button data-correct=\"false\">Reduce every dataset to exactly two dimensions.<\/button>\n  <button data-correct=\"false\">Generate only random predictions to prevent bias.<\/button>\n  <button data-correct=\"false\">Store records in a relational database hierarchy.<\/button>\n  <button data-correct=\"true\">Split data through a sequence of feature-based decision rules to make predictions.<\/button>\n  <button data-correct=\"false\">Calculate the mean of the target and ignore all inputs.<\/button>\n<\/div>\n\n<div class=\"question\" data-answered=\"false\">\n  <p>15. A Random Forest primarily improves upon a single decision tree by:<\/p>\n  <button data-correct=\"false\">Using only one deep tree with no randomness.<\/button>\n  <button data-correct=\"false\">Removing all features except the target.<\/button>\n  <button data-correct=\"false\">Replacing training data with test data.<\/button>\n  <button data-correct=\"false\">Guaranteeing zero prediction error.<\/button>\n  <button data-correct=\"true\">Combining predictions from many diverse decision trees.<\/button>\n<\/div>\n\n<div class=\"question\" data-answered=\"false\">\n  <p>16. What is the basic idea behind K-Nearest Neighbours (KNN)?<\/p>\n  <button data-correct=\"true\">Predict using the labels or values of nearby training examples in feature space.<\/button>\n  <button data-correct=\"false\">Always fit a straight line through the entire dataset.<\/button>\n  <button data-correct=\"false\">Create random clusters without measuring similarity.<\/button>\n  <button data-correct=\"false\">Use only a single global mean for all predictions.<\/button>\n  <button data-correct=\"false\">Train a language model on token sequences.<\/button>\n<\/div>\n\n<div class=\"question\" data-answered=\"false\">\n  <p>17. Naive Bayes classifiers rely on which simplifying assumption?<\/p>\n  <button data-correct=\"false\">All features must be perfectly correlated.<\/button>\n  <button data-correct=\"true\">Features are conditionally independent given the class.<\/button>\n  <button data-correct=\"false\">Every class must contain the same number of observations.<\/button>\n  <button data-correct=\"false\">The dataset must be unlabelled.<\/button>\n  <button data-correct=\"false\">No probability calculations are permitted.<\/button>\n<\/div>\n\n<div class=\"question\" data-answered=\"false\">\n  <p>18. What is the key objective of a Support Vector Machine classifier?<\/p>\n  <button data-correct=\"false\">Minimize the number of rows in the dataset.<\/button>\n  <button data-correct=\"false\">Create clusters by minimizing within-cluster variance only.<\/button>\n  <button data-correct=\"true\">Find a decision boundary that maximizes the margin between classes.<\/button>\n  <button data-correct=\"false\">Predict exclusively through majority class frequency.<\/button>\n  <button data-correct=\"false\">Transform every feature into text tokens.<\/button>\n<\/div>\n\n<div class=\"question\" data-answered=\"false\">\n  <p>19. Which method is an ensemble technique that builds learners sequentially to correct earlier errors?<\/p>\n  <button data-correct=\"false\">K-Means<\/button>\n  <button data-correct=\"false\">PCA<\/button>\n  <button data-correct=\"false\">Ordinary least squares without iteration<\/button>\n  <button data-correct=\"true\">Gradient Boosting<\/button>\n  <button data-correct=\"false\">Simple random sampling<\/button>\n<\/div>\n\n<div class=\"question\" data-answered=\"false\">\n  <p>20. A bank has historical customer data with a known label &#8216;churned&#8217; or &#8216;not churned&#8217;. Which learning setup is most appropriate?<\/p>\n  <button data-correct=\"false\">Unsupervised clustering<\/button>\n  <button data-correct=\"false\">Reinforcement learning without labels<\/button>\n  <button data-correct=\"false\">Dimensionality reduction only<\/button>\n  <button data-correct=\"false\">Association mining only<\/button>\n  <button data-correct=\"true\">Supervised classification<\/button>\n<\/div>\n\n\n\n    <!-- FINAL SUMMARY -->\n    <div class=\"final-summary\">\n      <h3>Quiz Summary <\/h3>\n\n      <div class=\"summary-row\">\n        <span>Attempted<\/span>\n        <div class=\"summary-bar\"><div class=\"bar-fill bar-attempted\" data-summary=\"attempted\"><\/div><\/div>\n        <span data-count=\"attempted\">0<\/span>\n      <\/div>\n\n      <div class=\"summary-row\">\n        <span>Correct<\/span>\n        <div class=\"summary-bar\"><div class=\"bar-fill bar-correct\" data-summary=\"correct\"><\/div><\/div>\n        <span data-count=\"correct\">0<\/span>\n      <\/div>\n\n      <div class=\"summary-row\">\n        <span>Wrong<\/span>\n        <div class=\"summary-bar\"><div class=\"bar-fill bar-wrong\" data-summary=\"wrong\"><\/div><\/div>\n        <span data-count=\"wrong\">0<\/span>\n      <\/div>\n\n      <div class=\"summary-row\">\n        <span>Unattempted<\/span>\n        <div class=\"summary-bar\"><div class=\"bar-fill bar-unattempted\" data-summary=\"unattempted\"><\/div><\/div>\n        <span data-count=\"unattempted\">0<\/span>\n      <\/div>\n\n      <div class=\"final-score\">\n        Final Score: <span class=\"score-value\" data-score>0.0<\/span>\n      <\/div>\n    <\/div>\n\n  <\/div>\n<\/div>\n<div class=\"modal modal-obls\" id=\"modal-signup\">\n        <div class=\"modal-background\"><\/div>\n        <div class=\"modal-content\">\n           <div class=\"obls-group\" id=\"obls-group1\">\n               <div class=\"obls-blk\">\n                   <span class=\"img-box\"><img decoding=\"async\" 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It covers Machine Learning types, data preprocessing, model evaluation, NLP, sentiment analysis, LLMs, Agentic AI, Responsible AI, cross-validation, overfitting, underfitting, and Reinforcement Learning. Candidates should focus on the basic concepts, working, and practical uses of these topics.<\/p>\n\n\n\n<figure class=\"wp-block-table\"><table><tbody><tr><th><strong>AI\/ML Area<\/strong><\/th><th><strong>Important Topics<\/strong><\/th><\/tr><tr><td>Machine Learning<\/td><td>Machine Learning, Introduction to ML Model<\/td><\/tr><tr><td>Learning Types<\/td><td>Supervised Learning, Unsupervised Learning, Reinforcement Learning<\/td><\/tr><tr><td>Data &amp; Models<\/td><td>Data Preprocessing, Model Evaluation<\/td><\/tr><tr><td>ML Concepts<\/td><td>Overfitting, Underfitting, Cross-Validation<\/td><\/tr><tr><td>NLP<\/td><td>NLP, Sentiment Analysis<\/td><\/tr><tr><td>Modern AI<\/td><td>LLM, Agentic AI<\/td><\/tr><tr><td>AI Ethics<\/td><td>Responsible AI<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"What_is_Machine_Learning\"><\/span>What is Machine Learning?<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>Machine Learning (ML) is a part of Artificial Intelligence that helps computers learn from data and improve without being programmed for every task. Candidates should understand the basic concepts of ML models and how they use data to find patterns and produce results.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"What_is_Supervised_Learning\"><\/span>What is Supervised Learning?<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>Supervised Learning is a type of Machine Learning in which a model learns from labelled data. The model uses the available input and known output to learn patterns and make predictions. Candidates should understand the basic concept and working of Supervised Learning.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"What_is_Unsupervised_Learning\"><\/span>What is Unsupervised Learning?<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>Unsupervised Learning is a type of Machine Learning in which a model works with data without predefined labels. It helps identify patterns or relationships within the available data. Candidates should understand the basic concept and working of Unsupervised Learning.<\/p>\n\n\n\n<p><strong>Also Check: <a href=\"https:\/\/www.oliveboard.in\/blog\/how-to-prepare-ai-ml-for-pfrda-grade-a\/?ref=contac-pfrda-ai-ml-pq\" target=\"_blank\" rel=\"noreferrer noopener\">How to prepare AI\/ML for PFRDA Grade A<\/a><\/strong><\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"What_is_Data_Preprocessing\"><\/span>What is Data Preprocessing?<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>Data Preprocessing refers to preparing data before it is used by a Machine Learning model. It helps make the data suitable for analysis and model development. Candidates should understand the basic purpose and importance of Data Preprocessing in Machine Learning.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"What_is_Model_Evaluation\"><\/span>What is Model Evaluation?<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>Model Evaluation is used to understand how well a Machine Learning model performs. It helps determine whether a model is producing suitable results based on the available data. Candidates should understand the basic concept and purpose of evaluating an ML model.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"What_are_Overfitting_and_Underfitting\"><\/span>What are Overfitting and Underfitting?<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>Overfitting occurs when a Machine Learning model learns the training data too closely and performs poorly on new data, while underfitting happens when it fails to learn important patterns. Candidates should understand the differences between overfitting and underfitting and their effects on model performance.<\/p>\n\n\n\n<figure class=\"wp-block-table\"><table><tbody><tr><th><strong>Concept<\/strong><\/th><th><strong>Meaning<\/strong><\/th><\/tr><tr><td>Overfitting<\/td><td>The model learns the training data too closely and performs poorly on new data.<\/td><\/tr><tr><td>Underfitting<\/td><td>The model fails to learn the important patterns in the data.<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"What_is_Cross-Validation_in_Machine_Learning\"><\/span>What is Cross-Validation in Machine Learning?<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>Cross-Validation is a technique used to evaluate the performance of a Machine Learning model. It involves using different parts of the available data for training and evaluation to get a better understanding of model performance. Candidates should understand the basic concept and purpose of Cross-Validation.<\/p>\n\n\n\n<div class=\"wp-block-buttons is-content-justification-center is-layout-flex wp-container-core-buttons-is-layout-16018d1d wp-block-buttons-is-layout-flex\">\n<div class=\"wp-block-button\"><a class=\"wp-block-button__link wp-element-button\" href=\"https:\/\/www.oliveboard.in\/pfrda-grade-a-exam\/?ref=contac-pfrda-ai-ml-pq\" target=\"_blank\" rel=\"noreferrer noopener\"><strong>Explore PFRDA Grade A Online Coaching Classes<\/strong><\/a><\/div>\n<\/div>\n\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"What_is_NLP_in_AIML\"><\/span>What is NLP in AI\/ML?<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>Natural Language Processing (NLP) is a field of Artificial Intelligence that enables computers to work with and understand human language. It is used in systems that process or analyse text and other forms of human language. Candidates should understand the basic concept and applications of NLP.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"What_is_Sentiment_Analysis\"><\/span>What is Sentiment Analysis?<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>Sentiment Analysis is an application of Natural Language Processing used to identify the sentiment or opinion expressed in text. It can help determine whether a piece of text expresses a positive, negative or neutral sentiment. Candidates should understand the basic concept and use of Sentiment Analysis.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"What_are_Large_Language_Models_LLMs\"><\/span>What are Large Language Models (LLMs)?<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>Large Language Models (LLMs) are AI models designed to understand and generate human language. They are used in various applications involving language and text. Candidates should understand the basic concept of LLMs and their role in modern AI systems.<\/p>\n\n\n\n<p><strong>Check: <a href=\"https:\/\/www.oliveboard.in\/blog\/major-changes-in-pfrda-grade-a-2026\/?ref=contac-pfrda-ai-ml-pq\" target=\"_blank\" rel=\"noreferrer noopener\">What are the major changes in the PFRDA Grade A 2026<\/a><\/strong><\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"What_is_Agentic_AI\"><\/span>What is Agentic AI?<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>Agentic AI refers to AI systems that can work towards a specific goal by making decisions and carrying out actions. Candidates should understand the basic concept of Agentic AI and how it differs from AI systems that only provide responses to user inputs.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"What_is_Responsible_AI\"><\/span>What is Responsible AI?<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>Responsible AI refers to the safe and responsible development and use of Artificial Intelligence systems. It focuses on ensuring that AI is developed and used appropriately. Candidates should understand the basic concept and importance of Responsible AI.<\/p>\n\n\n\n<div class=\"wp-block-buttons is-content-justification-center is-layout-flex wp-container-core-buttons-is-layout-16018d1d wp-block-buttons-is-layout-flex\">\n<div class=\"wp-block-button\"><a class=\"wp-block-button__link wp-element-button\" href=\"https:\/\/www.oliveboard.in\/blog\/pfrda-grade-a-practice-quiz\/?ref=contac-pfrda-ai-ml-pq\" target=\"_blank\" rel=\"noreferrer noopener\">Attempt PFRDA Grade A Practice Quiz<\/a><\/div>\n<\/div>\n\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"What_is_Reinforcement_Learning\"><\/span>What is Reinforcement Learning?<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>Reinforcement Learning is a type of Machine Learning in which an agent learns through interaction and feedback. The agent learns from the results of its actions and improves its decisions over time. Candidates should understand the basic concept and working of Reinforcement Learning.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-faqs\"><span class=\"ez-toc-section\" id=\"FAQs\"><\/span>FAQs<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<div class=\"schema-faq wp-block-yoast-faq-block\"><div class=\"schema-faq-section\" id=\"faq-question-1788857729710\"><strong class=\"schema-faq-question\">1. Is AI\/ML included in the PFRDA Grade A 2026 syllabus?<\/strong> <p class=\"schema-faq-answer\">Yes, AI\/ML is one of the new topics added to the General Stream Paper 2 syllabus in 2026.<\/p> <\/div> <div class=\"schema-faq-section\" id=\"faq-question-1788857730665\"><strong class=\"schema-faq-question\">2. What AI\/ML topics should candidates study for PFRDA Grade A?<\/strong> <p class=\"schema-faq-answer\">Candidates should study Machine Learning, Supervised and Unsupervised Learning, Data Preprocessing, Model Evaluation, NLP, Sentiment Analysis, Overfitting and Underfitting, LLMs, Agentic AI, Responsible AI, Cross-Validation, Introduction to ML Models, and Reinforcement Learning.<\/p> <\/div> <div class=\"schema-faq-section\" id=\"faq-question-1788883796941\"><strong class=\"schema-faq-question\">3. What is naive bayes in AI\/ML?<\/strong> <p class=\"schema-faq-answer\">Naive Bayes is a supervised Machine Learning algorithm that uses probability to classify data into different categories based on the available features.<\/p> <\/div> <div class=\"schema-faq-section\" id=\"faq-question-1788857731960\"><strong class=\"schema-faq-question\">4. What are the major Machine Learning types?<\/strong> <p class=\"schema-faq-answer\">The major types are supervised learning, unsupervised learning and reinforcement learning.<\/p> <\/div> <div class=\"schema-faq-section\" id=\"faq-question-1788857732576\"><strong class=\"schema-faq-question\">5. What should candidates study under Responsible AI?<\/strong> <p class=\"schema-faq-answer\">Candidates should revise fairness, accountability, transparency, explainability, privacy, security, safety and human oversight.<\/p> <\/div> <\/div>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n<ul class=\"wp-block-latest-posts__list is-grid columns-3 wp-block-latest-posts\"><li><a class=\"wp-block-latest-posts__post-title\" href=\"https:\/\/www.oliveboard.in\/blog\/pfrda-assistant-manager-previous-year-cut-off\/\">PFRDA Grade A Cut Off 2026, Previous Year Cut Off Score<\/a><\/li>\n<li><a class=\"wp-block-latest-posts__post-title\" href=\"https:\/\/www.oliveboard.in\/blog\/pfrda-assistant-manager-syllabus\/\">PFRDA Grade A Syllabus &amp; Exam Pattern 2026, Check Revised Details<\/a><\/li>\n<li><a class=\"wp-block-latest-posts__post-title\" href=\"https:\/\/www.oliveboard.in\/blog\/pfrda-assistant-manager-admit-card\/\">PFRDA Grade A Phase 2 Admit Card 2026, Download Hall Ticket PDF<\/a><\/li>\n<li><a class=\"wp-block-latest-posts__post-title\" href=\"https:\/\/www.oliveboard.in\/blog\/pfrda-assistant-manager-result\/\">PFRDA Grade A Result 2026, Download Grade A Scorecard PDF<\/a><\/li>\n<li><a class=\"wp-block-latest-posts__post-title\" href=\"https:\/\/www.oliveboard.in\/blog\/pfrda-grade-a-study-material\/\">PFRDA Grade A Study Material, Preparation Resources for Phase 1 &amp; 2<\/a><\/li>\n<li><a class=\"wp-block-latest-posts__post-title\" href=\"https:\/\/www.oliveboard.in\/blog\/pfrda-grade-a-pfrda-act-2013-quiz\/\">Attempt PFRDA Act 2013 Quiz for Grade A Exam &amp; Download PDF<\/a><\/li>\n<\/ul>","protected":false},"excerpt":{"rendered":"<p>The PFRDA Grade A 2026 AI\/ML Practice Quiz is designed to help candidates revise the newly added Artificial Intelligence and<\/p>\n","protected":false},"author":58,"featured_media":251062,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[11047,10247],"tags":[],"class_list":["post-251061","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-pfrda-grade-a","category-rbi-sebi-nabard","generate-columns","tablet-grid-50","mobile-grid-100","grid-parent","grid-50"],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v26.6 (Yoast SEO v26.6) - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Attempt PFRDA Grade A 2026 AI\/ML Practice Quiz and Download PDF<\/title>\n<meta name=\"description\" content=\"Attempt the PFRDA Grade A 2026 AI\/ML Practice Questions and boost your Paper 2 Exam prep for upcoming Exam Scheduled for 15th October 2026.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" 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I work as a Content Writer at Oliveboard, where I have been simplifying exam-related content for the past 4 years. I create clear and easy-to-understand guides for JAIIB, CAIIB, and UGC exams. My work includes breaking down notifications, admit cards, and exam updates, as well as preparing study plans and subject-wise strategies. My goal is to support working professionals in managing their exam preparation alongside a full-time job and to help them achieve career growth.\",\"sameAs\":[\"www.linkedin.com\/in\/aditi-chakraborty-131b3b379\"]},{\"@type\":\"Question\",\"@id\":\"https:\/\/www.oliveboard.in\/blog\/pfrda-grade-a-ai-ml-quiz\/#faq-question-1788857729710\",\"position\":1,\"url\":\"https:\/\/www.oliveboard.in\/blog\/pfrda-grade-a-ai-ml-quiz\/#faq-question-1788857729710\",\"name\":\"1. 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Is AI\/ML included in the PFRDA Grade A 2026 syllabus?","answerCount":1,"acceptedAnswer":{"@type":"Answer","text":"Yes, AI\/ML is one of the new topics added to the General Stream Paper 2 syllabus in 2026.","inLanguage":"en-US"},"inLanguage":"en-US"},{"@type":"Question","@id":"https:\/\/www.oliveboard.in\/blog\/pfrda-grade-a-ai-ml-quiz\/#faq-question-1788857730665","position":2,"url":"https:\/\/www.oliveboard.in\/blog\/pfrda-grade-a-ai-ml-quiz\/#faq-question-1788857730665","name":"2. What AI\/ML topics should candidates study for PFRDA Grade A?","answerCount":1,"acceptedAnswer":{"@type":"Answer","text":"Candidates should study Machine Learning, Supervised and Unsupervised Learning, Data Preprocessing, Model Evaluation, NLP, Sentiment Analysis, Overfitting and Underfitting, LLMs, Agentic AI, Responsible AI, Cross-Validation, Introduction to ML Models, and Reinforcement Learning.","inLanguage":"en-US"},"inLanguage":"en-US"},{"@type":"Question","@id":"https:\/\/www.oliveboard.in\/blog\/pfrda-grade-a-ai-ml-quiz\/#faq-question-1788883796941","position":3,"url":"https:\/\/www.oliveboard.in\/blog\/pfrda-grade-a-ai-ml-quiz\/#faq-question-1788883796941","name":"3. What is naive bayes in AI\/ML?","answerCount":1,"acceptedAnswer":{"@type":"Answer","text":"Naive Bayes is a supervised Machine Learning algorithm that uses probability to classify data into different categories based on the available features.","inLanguage":"en-US"},"inLanguage":"en-US"},{"@type":"Question","@id":"https:\/\/www.oliveboard.in\/blog\/pfrda-grade-a-ai-ml-quiz\/#faq-question-1788857731960","position":4,"url":"https:\/\/www.oliveboard.in\/blog\/pfrda-grade-a-ai-ml-quiz\/#faq-question-1788857731960","name":"4. What are the major Machine Learning types?","answerCount":1,"acceptedAnswer":{"@type":"Answer","text":"The major types are supervised learning, unsupervised learning and reinforcement learning.","inLanguage":"en-US"},"inLanguage":"en-US"},{"@type":"Question","@id":"https:\/\/www.oliveboard.in\/blog\/pfrda-grade-a-ai-ml-quiz\/#faq-question-1788857732576","position":5,"url":"https:\/\/www.oliveboard.in\/blog\/pfrda-grade-a-ai-ml-quiz\/#faq-question-1788857732576","name":"5. 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